Maintains a personal relationship with Jesus Christ
Develops, analyzes, and models operational, program, marketing, or other organizational data to analyze the competitive performance of Compassion's business segments
Develops innovative strategies, quantifies the competitive performance of the organization's operations and/or markets
Further evaluates potential operational changes, and designs new approaches and data methodologies accordingly
Applies and integrates statistical, mathematical, predictive modeling and business analysis skills to manage and manipulate complex high volume data from a variety of sources
Further tests and troubleshoots internal advanced analytics tools and data programs
Works closely with vendors to manage maintenance of data modeling tools
Performs exploratory data analysis to understand relationships, opportunities to influence outcomes and how to attribute cross-channel outcomes
Further develops proofs of concept to verify ideas and closes the loop to make sure that the proposed solution is performing as it should and is correctly understood by clients
Translates complex analytical and technical concepts for non-technical team members to enable understanding and drive informed business decisions
Collaborates with cross-functional teams across the organization to support data and cloud computing strategies

Proven experience operationalizing large backlogs of AI/ML use cases
Ability to establish AI best practices, standards, and reusable frameworks, enabling internal data scientists and analysts to deliver consistently
Strong background in exploratory data analysis and algorithm selection, with a focus on prioritizing measurable financial impact and business value
Demonstrated experience consolidating and rationalizing AI use cases across platforms, including savings calculations and alignment to enterprise technology strategy
Deep understanding of MLOps and production ML lifecycle, including model deployment, monitoring, governance, and integration with mature DevOps processes
Hands-on experience designing and orchestrating end-to-end AI systems across teams and platforms, not just isolated models or prompts
Proficiency with modern data and AI platforms, including AWS (SageMaker), Snowflake, DataRobot, Salesforce, and enterprise data warehouses
Experience implementing Retrieval Augmented Generation (RAG) and context-driven AI systems where prompts are augmented or replaced by governed data sources

Data Scientist III

Key skills